alg:coloc summarizes our COL method. The problem is
solved in an iterative fashion by alternating between E-step in eq:estep
and M-step in eq:mstep until convergence.
Following the common practice
in WSOD [1]}, [2]}, [3]}, we
use the bounding box feature extracted from the complete support images to initialize \({\mathbf {\theta }}\) .
Recall that we use the first proposal in \(F_i\)  to represent the complete image
feature. Thus, the initialization step can be written as
\({\mathbf {\theta }}_{\rm init} \leftarrow \rm {norm}(\sum _{i=1}^M F_{i1})~.\) 
